Authentication apparatus, authentication method, registration apparatus and registration method

ABSTRACT

An authentication apparatus includes: a vein data extracting unit that extracts vein data representing veins, from an image including the veins existing in a finger; an extracting unit that extracts position data representing the position which the contour of the finger has at an intermediate stage of extracting the vein data; and a determining unit that determines a collation candidate to be collated with the vein data, from the similarity between the position data and data associated with vein data to be registered.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present invention contains subject matter related to Japanese PatentApplications JP2008-002630 filed in the Japanese Patent Office on Jan.9, 2008, and JP2008-126207 filed in the Japanese Patent Office on May13, 2008, the entire contents of which being incorporated herein byreference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to an authentication apparatus, anauthentication method, a registration apparatus and a registrationmethod, which are suitable for use in biometric authentication.

2. Description of the Related Art

Systems are known, in which the data representing the entrance and exitof persons to and from a certain place is stored in a memory. The datamay be retrieved from the memory in order to determine whether a personwho has just input the data item identical to any data item registeredin the memory is indeed registered in the system. In this case,so-called “1:N authentication” is performed, whereby the data item inputand concerning the person is collated with the data items stored in thememory.

Authentication apparatuses of such a type have been proposed. (refer to,e.g., Jpn. Pat. Appln. Laid-Open Publication No. 2005-215883). Anyauthentication apparatus of this type generates a converted registrationimage of low-resolution image and a converted collation image oflow-resolution from registration images and collation images of a personto be authenticated. The authentication apparatus then determineswhether a registration image that is the source of a preset number ofconverted registration images that have high degree of correlation withthe converted collation image represents any person registered in theapparatus, from the result of collation between the registration imagesand the image of the person to authenticate.

SUMMARY OF THE INVENTION

In the authentication apparatus of this configuration, a convertedcollation image is generated from the collation image of the person toauthenticate. Therefore, whether the person has been registered or notcannot be determined unless a collation image of this person isgenerated. This decreases the authentication speed.

In this authentication apparatus, the converted registration image andthe converted authentication image are generated by the Huff transform.The Huff transform is a process of quantitatively finding, in a ρ-θspace, the linear components of an image (x-y plane image) that shouldbe converted.

The linear components quantitatively found include not only continuouslines, but also the line segments arranged in a straight line, forming abroken line (or a dotted line). That is, any registration image tocollate with the collation image of a person to authenticate isdetermined from the low degree of correlation based on the elements notcontained in the registration images or the collation images.Consequently, the registration image that is the source of convertedregistration images that have high degree of correlation with theconverted collation image may probably not include the registrationimage of the person registered. This inevitably decreases theauthentication speed.

The present invention has been made in view of the foregoing and aims toprovide an authentication apparatus, an authentication method, aregistration apparatus and a registration method.

According to an aspect of the present invention, there is provided anauthentication apparatus that includes: a vein data extracting unit thatextracts vein data representing veins, from an image including the veinsexisting in a finger; an extracting unit that extracts position datarepresenting the position which the contour of the finger has at anintermediate stage of extracting the vein data; and a determining unitthat determines a collation candidate to be collated with the vein data,from the similarity between the position data and data associated withvein data to be registered.

According to another aspect of the present invention, there is providedan authentication method that includes: a step of extracting vein datarepresenting veins, from an image including the veins existing in afinger; a step of extracting position data representing the positionwhich the contour of the finger has at an intermediate stage ofextracting the vein data; and a step of determining a collationcandidate to be collated with the vein data, from the similarity betweenthe position data and data associated with vein data to be registered.

According to yet another aspect of the present invention, there isprovided a registration apparatus that includes: a vein data extractingunit that extracts vein data representing veins, from an image includingthe veins existing in a finger; a key data extracting unit that extractskey data representing the state which the finger has at an intermediatestage of extracting the vein data; and a registering unit thatregisters, in a storage unit, the vein data in association with the keydata.

According to further another aspect of the present invention, there isprovided a registration method that includes: a vein data extractingstep of extracting vein data representing veins, from an image includingthe veins existing in a finger; a key data extracting step of extractingkey data representing the state which the finger has at an intermediatestage of extracting the vein data; and a registering step ofregistering, in a storage unit, the vein data in association with thekey data.

According to the present invention, the position a finger contour has atan intermediate stage of extracting vein data is used as an element fordetermining a collation candidate. The collation candidate can thereforebe determined before the vein data is extracted. Further, a collationcandidate can be accurately determined based on biometrical elementsdirectly, not influenced by pseudo elements such as Huff-transformimages. The invention can therefore realize an authentication apparatus,an authentication method, a registration apparatus, and a registrationmethod, which can operate at high speed.

The nature, principle and utility of the invention will become moreapparent from the following detailed description when read inconjunction with the accompanying drawings in which like parts aredesignated by like reference numerals or characters.

BRIEF DESCRIPTION OF THE DRAWINGS

In the accompanying drawings:

FIG. 1 is a block diagram showing the configuration of an authenticationapparatus according to an embodiment of the invention;

FIG. 2 is a block diagram showing the functional configuration (1) ofthe control unit when the authentication apparatus is working in thevein registration mode;

FIG. 3 is a block diagram showing the functional configuration (1) ofthe control unit when the authentication apparatus is working in theauthentication mode;

FIG. 4 is a block diagram showing the configuration of the vein dataextracting unit;

FIGS. 5A and 5B are diagrams explaining how the luminance changes in theprocess of extracting vein data;

FIG. 6 is a block diagram showing the configuration of the key dataextracting unit;

FIGS. 7A to 7D are schematic diagrams explaining how to extract datarepresenting the contour of the finger;

FIGS. 8A and 8B are schematic diagrams explaining how to extract aluminance histogram;

FIGS. 9A and 9B are schematic diagrams showing two images of the sameveins, acquired before and after the vein-width reducing process,respectively;

FIG. 10 is a block diagram showing the configuration (1) of theauthentication unit;

FIG. 11 is a flowchart illustrating the sequence of the authenticationprocess;

FIGS. 12A and 12B are schematic diagrams representing experimentalresults;

FIG. 13 is a schematic diagram showing the outer appearance of acellular telephone;

FIG. 14 is a schematic diagram showing the movable range of the cellulartelephone;

FIG. 15 is a diagram explaining how the user should place the finger,positioning the same with respect to the light source and base of thecellular telephone when the upper edge of an LCD is used as a reference;

FIG. 16 is a diagram explaining how the veins are imaged with thecellular telephone;

FIG. 17 is a block diagram showing the circuit configuration of thecellular telephone;

FIG. 18 is a block diagram showing the functional configuration (2) ofthe control unit working in the vein registration mode;

FIG. 19 is a block diagram showing the functional configuration (2) ofthe control unit working in the authentication mode;

FIG. 20 is a block diagram showing the configuration (2) of theauthentication unit;

FIGS. 21A and 21B are schematic diagrams explaining how the contour ofthe finger changes as the finger shifts in its lengthwise direction;

FIGS. 22A to 22C are schematic diagrams explaining how to calculate thechange in the finger contour by taking into account the shift of thefinger in its lengthwise direction;

FIG. 23 is a schematic diagram explaining the problem arising if acollation candidate is selected based on an estimated value of veindata; and

FIG. 24 is a schematic diagram explaining how to calculate theevaluation value of a registered set.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Embodiments of the present invention will be described in detail, withreference to the accompanying drawings.

(1) First Embodiment

(1-1) Circuit Configuration of Authentication Apparatus

FIG. 1 shows the circuit configuration of an authentication apparatus 1according to a first embodiment of the present invention. Theauthentication apparatus 1 includes a control unit 10, an operation unit11, an imaging unit 12, a storage unit 13, an interface 14, a displayunit 15, and an audio output unit 16. The units 12 to 16 are connectedto the control unit 10 via a bus 17. The operation unit 11 is directlyconnected to the control unit 10.

The control unit 10 is a computer composed of a central processing unit(CPU), a read only memory (ROM), and a random access memory (RAM). TheCPU controls the entire components of the authentication apparatus 1.The ROM stores various programs including an activation program. The RAMworks as a work memory for the CPU.

The operation unit 11 may be operated to input a command COM1 and acommand COM2 to the control unit 10. If the command COM1 is input to thecontrol unit 10, the authentication apparatus 1 will operate in a modeof registering the veins of a user (hereinafter called “registrant.”)(Hereinafter, this operating mode will be referred to as “veinregistration mode.”) If the command COM2 is input to the control unit10, the authentication apparatus 1 will operate in a mode of identifyingthe registrant. (Hereinafter, this operating mode will be referred to as“authentication mode.”)

From the command COM1 or COM2, the control unit 10 determines the modein which the apparatus 1 should operate. The control unit 10 thencontrols the imaging unit 12, storage unit 13, interface 14, displayunit 15 and audio output unit 16 in accordance with the programassociated with the command COM1 or COM2. The authentication apparatus 1therefore operates in either the vein registration mode or theauthentication mode.

The imaging unit 12 has a light source that applies light to the cushionof the registrant's finger laid on the light-input surface of theauthentication apparatus 1. The light applied passes the vein layer inthe finger, reaching the layer behind the vein layer. The light(hereinafter referred to as “near-infrared light”) includes beams havingwavelengths (700 nm to 900 nm), which are uniquely absorbed by bothdeoxygenated hemoglobin and oxygenated hemoglobin.

The imaging unit 12 generates, at regular intervals, video datarepresenting the image of the veins in the part of living body laid onthe light-input surface of the apparatus 1. The video data thusgenerated is supplied to the control unit 10.

The storage unit 13 is provided to store the data (hereinafter called“vein data”) about the veins included in an image to register. Thestorage unit 13 stores programs and various data items such setting dataitems. The storage unit 13 also stores data designated by the controlunit 10. Such data can be read from the storage unit 13.

The interface 14 can transmit and receive various data items to and fromany external apparatus connected to the authentication apparatus 1through a specific transmission path.

The display unit 15 displays, on a screen, the characters and figuresrepresented by the display data supplied from the control unit 10. Theaudio output unit 16 has a speaker generate sound based on the audiodata supplied from the control unit 10.

(1-1-1) Vein Registration Mode

The vein registration mode will be explained. Once the authenticationapparatus 1 has been set to the vein registration mode, the control unit10 causes the display unit 15 or the audio output unit 16, or both, togive a message, asking the registrant to place his or her finger on thelight-input surface of the apparatus 1. Then, the control unit 10functions as an imaging control unit 21, a vein data extracting unit 22,a key data extracting unit 23, and a registration unit 24, as isillustrated in FIG. 2.

The imaging control unit 21 drives the light source, which appliesnear-infrared light to the finger. In the finger, the near-infraredlight passes through the vein layer, reaching the layer behind the veinlayer. In the finger, the light is scattered and reflected. That part ofthe light, which is reflected, travels through the vein layer and skinsurface layer, back to the light-input surface of the authenticationapparatus 1. The near-infrared light traveling back to the light-inputsurface is guided to the imaging surface of the imaging unit 12. On theimaging surface, the near infrared light forms a high-contrast imagethat includes bright parts, i.e., the non-vein parts of the finger, anddark parts, i.e., the veins in the finger. The parts representing theveins are dark because the hemoglobin contained in the blood flowing inthe veins absorbs much light. (Hereinafter, those parts of the reflectedlight, which represent the veins, will be called generally “veinprojection light.”)

The imaging control unit 21 adjusts the position of an optical lens,bringing the images of veins to focus, based on the video data outputfrom the imaging unit 12. Further, the imaging control unit 21 adjuststhe opening of the diaphragm and the shutter speed (exposure time) forthe imaging element, based on a prescribed exposure value (EV).Therefore, the imaging unit 12 is set to imaging conditions that areoptimal to image the veins running in the finger placed on thelight-input surface.

Set to the optimal imaging conditions, the imaging control unit 21supplies to the video data given by the imaging unit 12, to the veindata extracting unit 22.

The vein data extracting unit 22 extracts vein data from the video datasupplied from the imaging control unit 21 and representing the veinimage. Thus, the vein data extracted is originated from the data outputof the imaging unit 12.

From the vein data extracting unit 22, the key data extracting unit 23acquires video data generated at a prescribed stage of the process ofextracting the vein data. The video data acquired is used as a key of acollation candidate. (Hereinafter, this video data will be also called“key data.”)

The registration unit 24 registers the vein data the vein dataextracting unit 22 has extracted, in association with the key dataextracted by the key data extracting unit 23, in the storage unit 13.

Thus, the control unit 10 registers in the storage unit 13 the vein dataand the key data representing a state the vein data assumes at theprescribed stage of the process of extracting the vein data, if theauthentication apparatus 1 is set to the vein registration mode.

(1-1-2) Authentication Mode

The authentication mode will be explained. Once the authenticationapparatus 1 has been set to the authentication mode, the control unit 10instructs the display unit 15 or the audio output unit 16, or both, togive a message, asking the registrant to place his or her finger on thelight-input surface of the apparatus 1. Then, the control unit 10 startsfunctioning as an imaging control unit 21, a vein data extracting unit22, a key data extracting unit 23, a reading unit 31, an authenticationunit 32, and a process executing unit 33, as is illustrated in FIG. 3 inwhich corresponding components are designated by the same referencenumerals as in FIG. 2.

The imaging control unit 21 drives the near infrared light source andsets the imaging unit 12 to imaging conditions. The vein data extractingunit 22 extracts vein data from the video data supplied from the imagingunit 12 via the imaging control unit 21, in the same way as in the veinregistration mode. The vein data about the registrant is thus extracted.

The storage unit 13 may store a plurality of vein data items about theregistrant. In this case, the key data extracting unit 23 acquires fromthe vein data extracting unit 22 the video data generated at the samestage in the vein registration mode of the process of extracting thevein data and then extracts key data in the same way as in the veinregistration mode.

The storage unit 13 may store only one vein data item about theregistrant. In this case, the reading unit 31 reads the vein data itemand supplies the same to the authentication unit 32. The authenticationunit 32 determines whether the user is an authenticated registrant ornot, from both the vein data that the reading unit 31 has read from thestorage unit 13 and the vein data the vein data extracting unit 22 hasextracted (in other words, whether the authentication has beensuccessfully accomplished or not).

On the other hand, the storage unit 13 may store a plurality of veindata items about the registrant. If this is the case, the reading unit31 reads the key data associated with the vein data items from thestorage unit 13 and supplies the key data to the authentication unit 32.The authentication unit 32 determines a collation candidate that shouldbe extracted by the vein data extracting unit 22, from both the key dataabout the registrant, which the data the reading unit 31 has read fromthe storage unit 13, and the key data about the registrant, which theextracting unit 23 has extracted.

The authentication unit 32 causes the reading unit 31 to read the veindata about the registrant, which has been determined as the collationcandidate. Using the vein data thus read and the vein data about theregistrant extracted by the vein data extracting unit 22, theauthentication unit 32 determines whether the user is an authenticatedregistrant (that is, whether the authentication has been successfullyaccomplished or not).

If the authentication unit 32 determines that the registrant isauthenticated (if the authentication has been successfullyaccomplished), the process executing unit 33 generates control data forstarting a specific process. The control data is supplied to an internalor external apparatus connected to the interface 14. The internal orexternal apparatus performs the specific process of, for example,keeping a door locked for a preset time or releasing the operating modeof a controlled object.

If the authentication unit 32 determines that the registrant is notauthenticated, the process executing unit 33 instructs the display unit15 or the audio output unit 16, or both, to give a message telling thatthe registrant is not authenticated.

Thus, using the vein data of the person to register and the key dataindicating the state the vein data of the person to authenticate has ata specific stage of the process of extracting the vein data, the controlunit 10 acquires a collation candidate that should be collated with thevein data of the person to authenticate while the authenticationapparatus 1 remains in the vein registration mode.

(1-2) Configuration of Vein Data Extracting Unit

The configuration of the vein data extracting unit 22 will be described.As shown in FIG. 4, the vein data extracting unit 22 includes an imagesmoothing unit 41, a contour emphasizing unit 42, a mask imagegenerating unit 43, an extracting unit 44, a vein smoothing unit 45, abinary coding unit 46, a line-thickening unit 47, and a line-thinningunit 48.

The image smoothing unit 41 has a spatial filter such as Gaussianfilter. The spatial filer performs filtering on the vein imagerepresented by the video data generated in the embodiments describedabove and supplied from the imaging control unit 21. The vein image isthereby rendered smooth.

The contour extracting unit 32 has a spatial filter such as Laplacian ofGaussian (Log) filter. This spatial filter performs filtering on thevein image smoothed by the image smoothing unit 41, emphasizing thecontour of the vein image.

The mask image generating unit 43 detects the contour of the finger fromthe vein image having the contour emphasized by the contour extractingunit 32, in accordance with the contrast the vein image has with respectto the background image. The mask image generating unit 43 generatesbinary data representing the finger region defined by the finger contourand the region lying outside the finger region. (Hereinafter, the imagerepresented by the binary data will be referred to as “mask image.”)

The extracting unit 44 uses the mask image generated by the mask imagegenerating unit 43, extracting an image of a preset size from the veinimage whose contour has been emphasized by the contour extracting unit32.

The vein smoothing unit 45 has a spatial filter such as a median filter.This spatial filter performs filtering on the vein image extracted bythe extracting unit 44, smoothing the images of veins in the vein image.

The binary coding unit 46 converts the vein image showing the veins thussmoothed by the vein smoothing unit 45, to a binary image, using apreset luminance as a threshold. Assume that the vein image showingveins not smoothed yet is converted to a binary image. Then, as shown inFIG. 5A, the image of each vein probably split into two veins at highprobability. Hence, binary data representing an image similar to theactual veins can be obtained as shown in FIG. 5B.

The line-thickening unit 47 has a spatial filter such as a dilationfilter. The dilation filter performs filtering on the binary vein videodata generated by the binary coding unit 46, increasing the thickness ofthe veins in the vein image. As a result, the veins are coupled,representing thicker veins.

The line-thinning unit 48 has a spatial filer such as an erosion filter.The erosion filter performs filtering on the thick vein image formed bythe line-thickening unit 47, making the thickness of the veins to afixed value.

Thus, the vein data extracting unit 22 extracts, as vein data, thebinary data that represents not only vein parts of the fixed thickness,but also the background part.

(1-3) Configuration of Key Data Extracting Unit

The configuration of the key data extracting unit 23 will be described.As shown in FIG. 6, the key data extracting unit 23 includes a selectionkey data extracting unit 51 and a selected-key data extracting unit 52.

The selection key data extracting unit 51 is a unit that extracts, as akey for selecting a collation candidate, the data representing the stateof the video data generated at an intermediate stage of the process thevein data extracting unit 22 performs. (Hereinafter, this data will alsobe referred to as “selection key data.”) The selection key dataextracting unit 51 has a contour extracting unit 61, a frequencydistribution extracting unit 62, and a blood-vessel area extracting unit63.

Using the vein image generated at the time of removing noise componentsfrom the image, the contour extracting unit 61 extracts the selectionkey data that represents the contour of the finger.

A concrete example of extracting technique will be explained. First, thecontour extracting unit 61 acquires a mask image (FIG. 7A) from the maskimage generating unit 43. Then, the unit 61 extracts a specific region(FIG. 7B) of the mask image, which represents the contour of the finger(i.e., pixels defining the finger contour).

The contour extracting unit 61 compresses the specific region (FIG. 7B)in vertical and horizontal directions, to one nth of the original size(FIG. 7C). The unit 61 then determines the position of the fingercontour (i.e., finger contour defined by pixels) that is contained inthe specific region compressed (FIG. 7C). The position thus determinedis a coordinate (x-coordinate) that represents the distance measuredfrom a reference line (i.e., left edge) and defined by the number ofpixels constituting a row or a column (FIG. 7D).

In this extracting technique, the coordinate value (x-coordinate) thatrepresents the distance from a reference line (i.e., left edge) and isdefined by the number of pixels constituting a row or a column is usedas the above-mentioned selection key data. Therefore, the datarepresenting the state (shape) of the finger contour can be smaller thanin the case where the selection key data is composed of the x-ycoordinates of the pixels constituting the finger contour.

Assume that the specific region to extract from the mask image iscomposed 240×30 pixels and that this region is compressed to one fifthof the original size. Then, in the compressed region composed of 48×6pixels, the position (coordinate value) the finger contour takes withrespect to the reference line is “48×1.” In this case, the selection keydata is composed of 24 bytes.

The frequency distribution extracting unit 62 extracts selection keydata by using the vein image generated at the time of removing noisecomponents from the image. The selection key data thus extractedrepresents the frequency distribution of the finger region defined bythe finger contour.

A concrete example of extracting technique will be explained. Thefrequency distribution extracting unit 62 acquires a vein image smoothedby the image smoothing unit 41. The unit 62 also acquires a mask imagefrom the mask image generating unit 43.

The frequency distribution extracting unit 62 uses the mask image,recognizing the finger region from the specific region in the smoothedvein image (FIG. 8A). Further, the unit 62 extracts pixels from thefinger region and classifies the pixels into groups, each composed ofpixels of the same luminance level (see FIG. 8B).

In this extracting technique, a luminance histogram of the finger regionin the smoothed vein image is used as selection key data. Hence, thefinger region can be represented by smaller data than in the case wherethe finger region per se is used as selection key data. Note that theselection key data is composed of 16 bytes, if the pixels are classifiedinto 16 bins, each assigned to a luminance level.

Moreover, in this extracting technique, the image to be extracted is avein image smoothed by the image smoothing unit 41. Therefore, thefinger region is less controlled in terms of luminance than in the casewhere the vein image is extracted after it has been supplied from theimage smoothing unit 41 and then processed by the contour emphasizingunit 42 or by the vein smoothing unit 45. The vein image can beextracted as selection key data that exhibits conspicuouscharacteristics.

The blood-vessel area extracting unit 63 extracts the selection key datarepresenting the area in the finger region defined by the fingercontour, by using the vein image represented by binary data andgenerated at a stage of the process of thickening the veins. A concreteexample of this extracting technique will be explained. First, theblood-vessel area extracting unit 63 acquires the binary datarepresenting a vein image of veins thickened, from the line-thickeningunit 47. Then, the unit 63 extracts selection key data representing thenumber of pixels defining the veins (blood-vessel area) from the veinimage.

Thus, in this extracting technique, the blood-vessel area in the imageof thickened veins, represented by binary data, is used as image fromwhich to determine the blood-vessel area. Therefore, the state of thefinger region can be represented by a smaller amount of data than in thecase where the blood vessels per se are used as selection key data. Notethat the selection key data is composed of two bytes.

As stated above, the binary image of thickened veins is used in thisextracting technique, as an image from which to extract the blood-vesselarea. The boundary between any blood vessel and any other part istherefore more distinct than in the case where the blood-vessel area isextracted from, for example, a multi-value vein image. As a result, theblood-vessel area can be extracted under a specific condition. FIG. 9Ashows an image of thickened veins, which is represented by binary data.This image shows the condition of the blood vessels more faithfully thansuch a vein image as shown in FIG. 9B, which is obtained by performing aline-thinning process on the binary data. The image of FIG. 9A cantherefore be extracted as selection key data that exhibits conspicuouscharacteristics of the veins.

The selection key data extracted by the selection key data extractingunit 51 is composed of a 24-byte block, a 16-byte block and a 2-byteblock, totaling 42 bytes. Even if 48 types of vein data items areregistered, the selection key data registered in the storage unit 13 inassociation with the vein data falls within one kbyte. The selection keydata therefore occupies, but an extremely small area in the storage unit13.

The selected-key data extracting unit 52 is a unit that extracts thedata (hereinafter called “selected key data”) representing the state ofthe vein image output from the vein data extracting unit 22 to beregistered. The fixed key data will be used as a key for determining acollation candidate.

More precisely, the selected-key data extracting unit 52 first extractsfrom the line-thinning unit 48 a vein image represented by binary dataincluding a vein part and a background part, the vein part being a partto register and having a fixed vein width. The unit 52 then compressesthe vein image to one nth (1/n) of the original size, generating acompressed image (hereinafter called “thumbnail image”). That is, theunit 52 extracts a thumbnail image as selected key data.

The selected key data reflects the contents of the entire vein imagethat should be registered. Therefore, the selected key data is key datathat represents the veins more in detail than the selected key dataextracted by the image smoothing unit 41, contour emphasizing unit 42 ormask image generating unit 43.

(1-4) Configuration of Authentication Unit

The configuration of the authentication unit 32 will be described. Asshown in FIG. 10, the authentication unit 32 includes a candidateselecting unit 71, a candidate determining unit 72, and a decision unit73.

The candidate selecting unit 71 compares the selection key data (i.e.,the position of the finger contour (coordinate value), the number ofpixels, each at a luminance level, and the number of pixels definingveins) read from the storage unit 13 by the reading unit 31 to beregistered, with the selection key data (i.e., the coordinate value ofthe finger contour, the number of pixels, each at a luminance level, andthe number of pixels defining veins) extracted by the key dataextracting unit 23 to be authenticated.

The candidate selecting unit 71 compares these selection key data itemsin terms of the number of pixels, each at a luminance level. First, theunit 71 finds a difference between the selection key data to beregistered (more precisely, the coordinate value of finger contour) andthe selection key data to be authenticated (more precisely, thecoordinate value of finger contour), in units of rows (or columns).Then, the unit 71 adds the absolute values of the differences found inunits of rows (or columns). The smaller the resultant sum is, the moresimilar the finger contours represented by the selection key data itemswill be. The sum of the absolute values will be referred to as“finger-contour difference value.”

Further, the candidate selecting unit 71 compares these selection keydata items in terms of the number of pixels, each at a luminance level.That is, the unit 71 compares the selection key data to be registered(more precisely, the number of pixels of each group, which are at aluminance level) and the selection key data to be authenticated (moreprecisely, the number of pixels of each group, which are at a luminancelevel). Then, the unit 71 selects the smaller of every two numbers ofpixels compared, and adds the numbers of pixels, thus selected. Thegreater the resultant sum is, the more similar the finger regionsrepresented by the selection key data items will be. The sum of thenumbers of pixels will be referred to as “finger region differencevalue.”

Moreover, the candidate selecting unit 71 compares these selection keydata items in terms of the number of pixels defining veins. First, theunit 71 finds a difference between the selection key data to beregistered (more precisely, the number of pixels defining veins) and theselection key data to be authenticated (more precisely, the number ofpixels defining veins) extracted by the selection key data extractingunit 51. The smaller the difference thus obtained, the larger the areathe veins occupy in the finger region. This difference will be referredto as “blood vessel difference value.”

Thus, the candidate selecting unit 71 obtains a finger-contourdifference value S, a finger region difference value H, and a bloodvessel difference value D. Two threshold values are set for thefinger-contour difference value S, i.e., first threshold value T1 andsecond threshold value T2. Also, one threshold value is set for theblood vessel difference value D, i.e., third threshold value T3. Then:

$\begin{matrix}{{{ES} = \frac{S}{T\; 1}}{{EH} = \frac{H}{T\; 2}}{{ED} = \frac{D}{T\; 3}}} & (1)\end{matrix}$

Thus, the ratio ES of finger-contour difference value S to the firstthreshold value T1, the ratio EH of finger region difference value H tothe second threshold value T2, and the ratio ED of blood vesseldifference value D to the third threshold value T3 are calculated,setting the finger-contour difference value, finger region differencevalue and blood vessel difference value within constant ranges (ornormalizing these three values).

Then, the candidate selecting unit 71 performs the followingcalculation:E=ES+ED−EH  (2)

That is, the candidate selecting unit 71 subtracts the ratio EH offinger region difference value H to the second threshold value T2 fromthe sum of the ratio ES of finger-contour difference value S to thefirst threshold value T1 and the ratio ED of blood vessel differencevalue D to the third threshold value T3. The unit 71 thereby generatesan evaluation value E. The smaller the finger-contour difference value Sand the blood vessel difference value D are, or the larger the fingerregion difference value H is, the higher the similarity will be. Hence,the smaller the evaluation value E is, the more probably the registrantwill be authenticated.

Thus, the candidate selecting unit 71 detects the selection key datahaving an evaluation value smaller than the fourth threshold value setfor the evaluation value E, and selects the vein data to register andassociated with the selection key data detected, as a collationcandidate that will be collated with the vein data that should beauthenticated.

The candidate selecting unit 71 compares the number of collationcandidates thus far selected, with a preset number of collationcandidates (hereinafter referred to as “preset number of candidates”).If the number of collation candidates selected is equal to or greaterthan the preset number of candidates, the collation candidates selectedwill be collated in the descending order of evaluation value E.

Assume that the number of collation candidates selected is smaller thanthe preset number of candidates. Then, the vein data items selected ascollation candidates to register may include a data item eitheridentical, or considered to be identical, to the vein data to beauthenticated. In this case, the candidate selecting unit 71 selectsagain the preset number of candidates in the descending order ofevaluation value E, and sets an order in which to collate the collationcandidates thus selected.

That is, the candidate selecting unit 71 is designed to select vein dataitems and to set the order in which to collate these vein data items, ascandidates, with the vein data that should be authenticated, by usingthe similarity of a part (i.e., finger contour, finger region, or veinpart) of the image extracted to be registered or authenticated, asreference for selecting the collation candidates, and to set the orderin which to collate the collation candidates selected.

If the number of collation candidates is smaller than the preset numberof candidates, the candidate selecting unit 71 selects the vein dataitems in the descending order of similarity, no matter whether thecollation candidates have similarity (in terms of shape, luminance,number of vein pixels) lower than a preset level (i.e., fourth thresholdvalue). This increases the chance of a selecting collation candidateidentical or considered to be identical to the vein data to beauthenticated.

Note that the vein contour varies, depending on how much the finger tipis bent or how thick the finger is. Therefore, the candidate selectingunit 71 excludes, as collation candidates, the vein data items whichdiffer in terms of the type of the finger authenticated and the growthof finger.

The luminance of the finger region varies from person to person, inaccordance with the thickness of the finger, the race of the registrant,such as Black or Caucasian. This is why the candidate selecting unit 71roughly excludes, as collation candidates, the vein data items whichdiffer in the type of the finger authenticated and the growth of finger,in accordance with the luminance of the finger region.

Further, the blood-vessel area differs from person to person, inaccordance with, for example, sex, fat content or finger thickness.Therefore, the candidate selecting unit 71 roughly excludes, ascollation candidates, the vein data items which differ in the type ofthe finger authenticated and the sex of the registrant.

The candidate determining unit 72 determines one collation candidate, orselects one of the collation candidates selected by the candidateselecting unit 71 in numbers equal to or larger than the preset number,by using the fixed key data (thumbnail image) associated with the veindata of the collation candidate to be registered and the fixed key data(thumbnail image) to be authenticated, which has been extracted by thekey data extracting unit 23.

More specifically, the candidate determining unit 72 causes the readingunit 31 to read the fixed key data items to be registered, in the orderset by the candidate selecting unit 71. Every time the reading unit 31reads fixed key data (thumbnail image), the unit 72 collates the fixedkey data with the fixed key data item (thumbnail images) to beauthenticated. In this process of collating a fixed key data (thumbnailimage) with the fixed key data item to be authenticated, the similarity(or degree of difference) of the fixed data is determined in the formof, for example, a mutual collation function, a phase collationfunction, or a sum of absolute difference (SAD).

The result of the collation of the fixed key data items (thumbnailimages) compared with each other, one to be registered and the other tobe authenticated, may be equal to or greater than the fifth thresholdvalue set for this result. If this is the case, the candidatedetermining unit 72 determines the vein data to be registered andassociated with the thumbnail image, as a collation candidate of thevein data that should be authenticated.

That is, the candidate determining unit 72 is configured to determinethe vein data as a candidate to collate with the vein data to beauthenticated, by using, as collation-candidate determining reference,the similarity of the fixed key data (thumbnail image) acquired from thevein data extracted at the time registration and authentication andrepresenting the veins more in detail than the selected key data.

The decision unit 73 collates the vein data the candidate determiningunit 72 has determined as a collation candidate, with the vein data thevein data extracting unit 22 has extracted as vein data to beauthenticated. Based on the result of this collation, the decision unit73 determines whether the user is an authenticated registrant or not. Inthis collation of the vein data items, reference data identical to thefixed key data (thumbnail image) or any other data may be used.

(1-5) Sequence of Authentication Process

The sequence of the authentication process the authentication unit 32performs will be explained. As shown in FIG. 11, the authentication unit32 starts performing the authentication process when the authenticationapparatus 1 is set to the authentication mode. In Step SP1, theauthentication unit 32 acquires selection key data to register andselection key data to authenticate. The process then goes to Step SP2.

In Step SP2, the authentication unit 32 compares the selection key datato register with the selection key data to authenticate, generating anevaluation value. The authentication unit 32 generates the evaluationvalue indicating that the smaller the difference between the selectionkey data items compared, the more greatly the selection key data itemsare evaluated as collation candidates. Then, the process goes to StepSP3.

In Step SP3, the authentication unit 32 detects selection key data toregister, which has an evaluation value smaller than a prescribed value,and selects the vein data associated with the selection key data thusdetected, as a collation candidate to be collated with the vein datathat should be authenticated. The process then goes to Step SP4, inwhich the authentication unit 32 determines whether the number of suchcollation candidates selected is equal to or greater than a prescribednumber (preset candidate number).

The number of collation candidates selected may be equal to or greaterthan the preset candidate number. In this case, the authentication unit32 determines that the vein data items selected as collation candidatesto register may include a data item either identical, or considered tobe identical, to the vein data to be authenticated with highpossibility. In this case, the process goes to Step SP5. In Step SP5,the selecting unit 71 selects again the preset candidate number in thedescending order of evaluation value. The authentication unit 32 goes toStep SP6, skipping Step SP5.

The number of collation candidates selected may be smaller than thepreset candidate number. In this case, the authentication unit 32determines that the vein data items selected as collation candidates toregister may not include a data item either identical, or considered tobe identical, to the vein data to be authenticated. If this is the case,the process goes to Step SP5. In Step SP5, the selecting unit 71 selectsagain the preset number of candidates in the descending order ofevaluation value. The authentication unit 32 then goes to Step SP6.

In Step SP6, the authentication unit 32 sets the collation candidatesgenerated in Step SP2, in descending order. In Step SP7, theauthentication unit 32 acquires fixed key data items associated with thevein data to register and used as collation candidates, and acquiresfixed key data to authenticate.

The authentication unit 32 then goes to Step SP8 and collates the fixedkey data with the fixed key data items to authenticate in the order setin Step SP6. Thus, the authentication unit 32 determines, as a collationcandidate, the vein data item associated with the fixed key data whichshould be registered and which represents similarity equal to or higherthan a preset value, with respect to the fixed key data to authenticate.

In Step SP9, the authentication unit 32 collates the vein data items toregister determined as collation candidates with the vein data toauthenticate. In Step SP10, the authentication unit 32 determineswhether the user is an authenticated registrant or not. Then, the unit32 terminates the authentication process.

Thus, the authentication unit 32 is configured to use the selection keydata, reducing the number of collation candidates, and then to use thefixed key data more minute than the selection key data, further reducingthe number of collation candidates.

(1-6) Operation and Effect

The authentication apparatus 1 having the configuration described aboveextracts key data representing the position the finger contour takes atan intermediate stage of the process of extracting the vein data toregister, and stores the key data in the reading unit 31, in associationwith the vein data.

The authentication apparatus 1 further extracts key data representingthe position the finger contour takes at an intermediate stage of theprocess of extracting the vein data to register to authenticate. Theapparatus 1 then determines one of the vein data items to register, as acandidate to collate with the vein data to authenticate, in accordancewith the similarity with the key data registered in the storage unit 13.

Thus, in the authentication apparatus 1, the position the finger contourtakes at an intermediate stage of the process of extracting the veindata is an element that determines the collation candidate. Theauthentication apparatus 1 can therefore determine the collationcandidate during the process of extracting the vein data toauthenticate. Thus the authentication apparatus 1 can authenticate theuser at high speed. Since the data representing the position of thefinger contour pertains to the elements of a living body, not containingpseudo elements such as Huff-transform images. This minimizes thepossibility that the collation candidates include no registered imagesof the registrant. The authentication apparatus 1 can thereforeauthenticate the user at high speed.

In the authentication apparatus 1, the positions of the pixels which arespaced at regular intervals (FIG. 7C) among the pixels defining thefinger contour are extracted from the specific region of an imagegenerated at an intermediate stage of the process of extracting the veindata as finger-contour position data.

The authentication apparatus 1 can therefore display the finger contourwith a smaller amount of data than in the case where the positions ofthe pixels (FIG. 7B) are used as data representing the finger contour.As a result, the area the data occupies in the storage unit 13 can bereduced. At the same time, the load of determining the similarity of thefinger-contour position data can be reduced.

In the authentication apparatus 1, the positions of the pixels spaced atregular intervals are defined by the coordinate value (x-coordinates)that represents the distance from a reference line (i.e., left edge, notthe x-coordinates and y-coordinates (see FIG. 7D). Further, small amountof data can therefore define the finger contour.

In the authentication apparatus 1, the image generated at the stage ofremoving noise components from the image showing veins in the finger (orgenerated in the image smoothing unit 41) is used as image from which toextract the data representing the position of the finger contour. Thefinger contour can therefore be extracted more accurately from the imagethat is free of pseudo elements resulting from instantaneous changes in,for example, the imaging conditions. This further reduces thepossibility that the collation candidates include no registered imagesof the registrant.

In the authentication apparatus 1, not only the data representing thefinger contour, but also the data representing the frequencydistribution of the finger region defined by the finger contour and thedata representing the vein area in the region defined by the fingercontour are extracted. Therefore, the authentication apparatus 1 candetect the characteristics of the living body from various points ofview. Thus, even if the data representing each characteristic is smallin amount, the probability that none of the collation candidates includethe registered image of the registrant can be reduced far more readilythan in the case where the data represents only the finger contour.

FIGS. 12A and 12B are graphs showing the results of an experiment, inwhich vein images (200 images) of 50 persons were registered. In thesegraphs, the data representing the finger contour, the data representingthe frequency distribution of the finger region defined by the fingercontour and the data representing the vein area in the region defined bythe finger contour, for each person, are three-dimensionally plotted. Asseen from FIGS. 12A and 12B, the gray marks (pertaining to one person)lie at the corners of the group of black marks (pertaining to anotherpersons). This indicates that the probability that none of the collationcandidates include the registered image of the registrant is extremelylow.

In the authentication apparatus 1, the similarity between the three dataitems, respectively representing the finger contour, the frequencydistribution of the finger region defined by the finger contour and thevein area in the region defined by the finger contour, is obtained bysubtracting the ratio EH of finger region difference value H to thesecond threshold value T2 from the sum of the ratio ES of finger-contourdifference value S to the first threshold value T1 and the ratio ED ofblood vessel difference value D to the third threshold value T3, as beenfrom the equations (1) and (2).

Hence, in the authentication apparatus 1, the similarity can becalculated by performing simple operations such as addition andsubtraction, not by performing complicated statistical operations usingdispersion and standard deviation in order to attain correlationcoefficients. As a result, the authentication can be achieved evenfaster than otherwise.

Further, in the authentication apparatus 1, collation candidates areselected in accordance with the similarity between selection key dataitems (i.e., the finger contour, the frequency distribution of thefinger region defined by the finger contour, and the vein area in theregion defined by the finger contour). Then, one of the selectedcollation candidates is determined is selected in accordance with thesimilarity of the fixed key data (thumbnail image) that is larger inamount than the selection key data.

Thus, the number of collation candidates is first reduced and thenfurther minutely reduced in the authentication apparatus 1. Theauthentication apparatus 1 can therefore authenticate any registrant athigher speed than in the case where a collation candidate is determinedfrom only the selection key data or the fixed key data, and can yetminimize the possibility that the collation candidates include noregistered images of the registrant.

The time required to calculate the similarity of the selection key datawas 0.01 msec or less for one vein image on MATLAB7.4.0. When everyfourth image (N/4) was selected as a collation candidate from N images,and every second (N/8) of the images thus selected was selected as acollation candidate, the time required to calculate the similarity was 3msec on MATLAB7.4.0. The time required to collate the candidate thusdetermined with the vein data to authenticate and to determine whetherthe user is an authenticated registrant was 10 msec on MATLAB7.4.0.

Thus, the average time for the above-mentioned authentication istheoretically 0.01·N msec+3N/8 msec+10 msec, or 0.3651N+10 msec. On theother hand, the average time for the authentication in which a collationcandidate is determined from only the fixed key data (thumbnail image),not using the selected key data, is 1.5N+10 msec.

That is, if some collation candidates are first selected by using theselection key data and then further selected by using the fixed key, theauthentication can be achieved about four times faster than in the casewhere a collation candidate is determined from the fixed key data only.

In the authentication apparatus 1 so configured as described above, acollation candidate is selected in accordance with the finger contourextracted at an intermediate stage of the process of extracting the veindata. That is, the collation candidate can be selected while the veindata to be authenticated is being extracted. This reduces theprobability that none of the collation candidates include the registeredimage of the registrant, more than in the case where data containingpseudo elements is used to select a collation candidate. Theauthentication apparatus 1 can thus authenticate the registrant at highspeed.

(2) Second Embodiment

(2-1) Outer Appearance of Cellular Phone

FIG. 13 shows the outer appearance of a cellular telephone 100 accordingto a second embodiment of this invention. The cellular telephone 100includes a first housing 102, a second housing 103, and a hinge unit104. The first housing 102 and second housing 103 have substantially arectangular parallelepiped shape.

A liquid crystal display (LCD) 111 is provided on the center part of onesurface P1 of the first housing 102. A speaker 112 is provided in thatpart of the surface P1 which opposes the channel-shaped part of thesurface P1.

The second housing 103 has a surface P2. On the center part of thesurface P2, an operation unit 113 is provided. The operation unit 113has a power key, a call key, menu keys, and character keys. Theprojecting part of the surface P2, which lies in the channel-shaped partof the surface P1 of the first housing 102, has an imaging window 114. Amicrophone 115 is provided in that end of the surface P2, which opposesthe projecting part.

The hinge unit 104 has an axle that penetrates the channel-shaped partof the first housing 102 and the projecting part of the second housing103. Around the axle, the first housing 102 or the second housing 103can rotate, as shown in FIG. 14, between a position (hereinafter called“closed position”) where the surfaces P1 and P2 oppose each other and anopened position (hereinafter called “opened position”) where thesurfaces P1 and P2 define a predetermined angle between then.

The cellular telephone 100 is so designed that the projecting part ofthe second housing 103 remains exposed while the cellular telephone 100stays in not only the closed position, but also the opened position. Anobject can therefore be imaged through the imaging window 114 no matterwhether the cellular telephone 100 is in the closed position or theopened position.

Moreover, the cellular telephone 100 is so configured that the lightreflected by the blood vessels in the finger placed at a specifiedposition on the first housing 102 passes through the imaging window 114.That is, a light source unit 121 is arranged between the upper edge ofthe LCD 111 and a speaker 112, and a pair of bases 122 (bases 122 a and122 b), either shaped like a thin plate, are provided on the sides of anupper part of the LCD 111, respectively.

This arrangement of the bases 122 a and 122 b and the positionalrelation the bases 122 have with the light source unit 121 enable theuser to understand that he or she should place his or her finger on thedisplay screen, not on the speaker 112 as shown in FIG. 15. In addition,the bases 122 prevent the user's finger from contacting the displayscreen of the LCD 111, ultimately preventing dirt, such as sweat, fromsticking to the display screen.

Assume that the user places his or her finger at the specified positionon the first housing 102 while the first housing 102 remains in theopened position as shown in FIG. 16. Then, the near infrared lightemitted from the light source unit 121 passes through the vein layer inthe finger, reaching the layer behind the vein layer. In the finger, thelight is scattered and reflected. The light reflected or scatteredemerges from the finger.

That part of the near infrared light emerging from the finger, whichtravels parallel or substantially parallel to the surface P1 of thefirst housing 102, passes through the imaging window 114. In the secondhousing 103, the near infrared light is guided by an optical system to acharge coupled device (CCD). That part of the near infrared light, whichhas passed through the non-vein parts in the finger (has not passedthrough the vein layer) form a bright image. On the other hand, the partof the near infrared light, which has passed through the vein parts inthe finger (has passed through the vein layer), form a dark imagebecause the hemoglobin absorbs light.

(2-2) Circuit Configuration of Cellular Telephone

The circuit configuration of the cellular telephone 100 will bedescribed. As shown in FIG. 17 in which some components are designatedby the same reference numerals as in FIG. 13, an LCD 111, a speaker 112,a microphone 115, a CCD 131, a storage unit 132, and a communicationsunit 133 are connected to a control unit 130 via a bus 134.

The control unit 130 is a computer that includes a CPU, a ROM, and aRAM. The CPU controls the entire components of the cellular telephone100. The RON stores various programs including an activation program.The RAM functions as a work memory for the CPU.

The control unit 130 can receive various instructions from the operationunit 113. The instructions include an instruction for executing theblood-vessel registration mode, an instruction for executing theauthentication mode, an instruction for executing the electronic-mailpreparation/transmission mode, and an instruction for executing thecommunication mode.

The control unit 130 determines the operating mode to execute, from theinstruction it has received. In accordance with the program associatedwith the operating mode, the control unit 130 controls the LCD 111,speaker 112, microphone 115, CCD 131, storage unit 132 andcommunications unit 133, thereby to perform various processes.

The LCD 111 is configured to display on the display screen the contentsuch as characters and figures, which is represented by the display datasupplied from the control unit 130. The speaker 112 can generate aspeech represented by the audio data supplied from the control unit 130.The microphone 115 catches a speech and converts the speech to audiodata in a predetermined cycle. The audio data is output to the controlunit 130.

The CCD 131 receives the light coming through the imaging window 114(FIG. 13) and performs photoelectric conversion on the light at regularintervals. Thus, the CCD 131 converts the light to video data. The videodata is sent to the control unit 130.

The storage unit 132 is provided to hold various data items, such asvein data, programs and setting data. The storage unit 132 is configuredto store any data designated by the control unit 130. The data can beread from the storage unit 132.

The communications unit 133 receives various data items from themicrophone 115 or the control unit 130. The unit 133 performs a specificmodulation process on the data and amplifies the data, therebygenerating a signal. The signal thus generated is transmitted, as anuplink signal, from the antenna ANT of the cellular telephone 100 to abase station (not shown).

The communications unit 133 receives a downlink signal transmitted fromthe base station (not shown) via the antenna ANT. The unit 133 amplifiesthe downlink signal and then performs a specific demodulation process onthe downlink signal, generating data. This data is supplied to thespeaker 112 or the control unit 130.

(2-2-1) Vein Registration Mode

The vein registration mode will be explained next. The control unit 130may determine that the vein registration mode should be executed. Inthis case, the control unit 130 causes the LCD 111 or the speaker 112,or both, to tell the user to move the first and second housings 102 and103 to the opened position (FIG. 16) and then place his or her finger onthe display screen, stretching it along the upper edge of the LCD 111(FIG. 15).

Thereafter, the control unit 130 functions as an imaging control unit21, a vein data extracting unit 22, a key data extracting unit 23, and aregistration unit 140, as is illustrated in FIG. 18. The imaging controlunit 21, vein data extracting unit 22 and key data extracting unit 23are identical to those shown in FIG. 2. Therefore, only the registrationunit 140 having different configuration as the registration unit 24 inthe first embodiment will be described below.

The registration unit 140 determines whether the vein data is fit toregister, from the amount of the vein data extracted by the vein dataextracting unit 22 and the shape of the vein pattern. If the vein datais found fit to register, the registration unit 140 determines whetherthe number of vein data items the registrant should register has reachedtwo or more.

If the vein data is not found fit to register or if the number of veindata items fit to register has not reached the preset value, theregistration unit 140 notifies this fact through the LCD 111 or thespeaker 112, or both.

If the number of vein data items fit to register has reached the presetvalue, the registration unit 140 stores, in the storage unit 132, thevein data items and key data items the key data extracting unit 23 hasextracted from the image, with each vein data item in association withthe key data item. (The set of each vein data item and the associatedkey data item will be called “registered set”.)

The registration unit 140 thus stores each vein data item in associationwith a key data item. In view of this, the registration unit 140 differsfrom the registration unit 24 of the first embodiment, which registersthe vein data about a finger and the key data about the finger.

(2-2-2) Authentication Mode

The authentication mode will be explained next. Once the cellulartelephone has been set to the authentication mode, the control unit 130instructs the LCD 111 or the speaker 112, or both, asking the registrantto move the first and second housings 102 and 103 to the opened position(FIG. 16) and to place his or her finger on the display screen, alongthe edge of the LCD 111 (FIG. 15).

If the storage unit 132 stores one registered set, the reading unit 31supplies the vein data contained in the registered set to anauthentication unit 150. The authentication unit 150 determines whetherthe user is the registrant, by using the vein data read by the reddingunit 31, which should be registered, and the vein data extracted by thevein data extracting unit 22, which should be authenticated. (In otherwords, the authentication unit 150 determines whether the authenticallyhas been successfully accomplished or not.)

On the other hand, if the storage unit 132 stores a plurality ofregistered sets, the reading unit 31 supplies the key data which isassociated with the vein data contained in each registered set and whichshould be registered.

In this case, the authentication unit 150 selects, from the registeredsets stored in the storage unit 132, the registered set that should becollated with the vein data which has been extracted by the vein dataextracting unit 22 and which should be authenticated, based on the keydata to register read by the reading unit 31 and the key data toauthenticate extracted by the key data extracting unit 23.

The authentication unit 150 causes the reading unit 31 to read the veindata contained in the registered set determined to be a collationcandidate. Using the vein data thus read and the vein data toauthenticate extracted by the vein data extracting unit 22, theauthentication unit 150 determines whether the user is the registrant ornot. (That is, the unit 150 determines whether the authentication hasbeen successfully accomplished or not.)

Thus, the authentication unit 150 determines collation candidates inaccordance with the vein data units contained in registered sets. Inthis respect, the authentication unit 150 differs from theauthentication unit 32 of the first embodiment, which determinescollation candidates in accordance with the individual vein data items.The process the authentication unit 150 performs will be explained infollowing paragraph.

(2-3) Configuration of Authentication Unit

The configuration of the authentication unit 150 will be described withreference to FIG. 20, in which the components identical to those shownin FIG. 10 are designated by the same reference numbers. As FIG. 10shows, the authentication unit 150 includes a candidate selecting unit160, a candidate determining unit 72, and a decision unit 73. Only thecandidate selecting unit 160 having different configuration as thecandidate selecting unit 71 in the first embodiment will be explained.

The candidate selecting unit 160 compares the selection key data (i.e.,the position of the finger contour (coordinate value), the number ofpixels of each luminance level, and the number of vein pixels) which hasbeen read by the reading unit 31 from the storage unit 132 and whichshould be registered, with the selection key data (i.e., the position ofthe finger contour (coordinate value), the number of pixels of eachluminance level, and the number of vein pixels) which has been extractedby the key data extracting unit 23 and which should be authenticated.

The candidate selecting unit 160 takes the lengthwise shift of thefinger into consideration, in comparing the selection key data thatindicates the coordinate value of the finger contour. In this respect,the candidate selecting unit 160 differs from the candidate selectingunit 71 of the first embodiment, which does not take the shifting of thefinger into account at all.

The candidate selecting unit 71 finds a difference between the selectionkey data to be registered (i.e., the coordinate value x of fingercontour) and the selection key data to be authenticated (i.e., thecoordinate value x of finger contour), in units of rows (or columns).Hence, the finger contour will change as shown in FIGS. 21A and 21B whenthe finger extending along the upper edge of the LCD 111 is moved in thelengthwise direction after the selection key data is registered andbefore the vein data is authenticated, even if the user is theregistrant.

In this case, the difference between the selection key data itemscompared is large through the user is the registrant. Consequently, thevein data of the registrant may not be selected, though it should beselected as a collation candidate.

The candidate selecting unit 160 uses either the selection key data toregister or the selection key data to authenticate (i.e., coordinatevalue x of finger contour), as data about a shifting object. Forexample, as shown in FIGS. 22A to 22C, the selection key data SK aboutthe shifting object (i.e., coordinate value x of finger contour) ismoved, at a prescribed pitch, from the start position (FIG. 22A) to theend position (FIG. 22B) in the lengthwise direction of the finger.

The candidate selecting unit 160 obtains an average of theabsolute-value differences at the positions (including the start and endpositions) to which the object has been shifted in the finger contour(over the range indicated by arrows in FIGS. 22A to 22C). The minimumvalue obtained is applied as finger-contour difference value. Of thecases of FIG. 22A to 22C, the case of FIG. 22A has the minimum value.

More specifically, the candidate selecting unit 160 obtains thefinger-contour difference value, using the following equation:

$\begin{matrix}{s = {\min\left( {{\sum\limits_{p = 1}^{l_{v} - {lS}_{\max}}\frac{{S_{({r,p})} - S_{({i,{p + {lS}_{\max}}})}}}{\left( {l_{v} - {lS}_{\max}} \right)}},{\sum\limits_{p = 1}^{l_{v} - {lS}_{\max} + 1}\frac{{S_{({r,p})} - S_{({i,{p + {({{lS}_{\max} - 1})}}})}}}{\left( {l_{v} - {lS}_{\max} + 1} \right)}},\ldots\mspace{14mu},{\sum\limits_{p = 1}^{l_{v}}\frac{{S_{({r,p})} - S_{({i,p})}}}{l_{v}}},{\sum\limits_{p = 2}^{l_{v}}\frac{{S_{({r,p})} - S_{({i,{p - 1}})}}}{\left( {l_{v} - 1} \right)}},\ldots\mspace{14mu},{\sum\limits_{p = {lS}_{\max}}^{l_{v}}\frac{{S_{({r,p})} - S_{({i,{p - {({{lS}_{\max} - 1})}}})}}}{\left( {l_{v} - {lS}_{\max} + 1} \right)}},{\sum\limits_{p = {{lS}_{\max} + 1}}^{l_{v}}\frac{{S_{({r,p})} - S_{({i,{p - {({lS}_{\max})}}})}}}{\left( {l_{v} - {lS}_{\max}} \right)}}} \right)}} & (3)\end{matrix}$

where “lv” is the length of the finger contour, lSmax is the maximumshift, p is the index (position) defining the finger contour, and S isthe finger-contour difference value for the index p.

In the equation (3), r is an object to register, and I is an object toauthenticate.

Thus, the candidate selecting unit 160 takes, into account, thelengthwise shift of the finger that should be placed at a specificposition.

To compare selection key data items, each representing the number ofpixels of a luminance level, or selection key data items, eachrepresenting the number of vein image pixels, the candidate selectingunit 160 obtains finger region difference value and a blood vesseldifference value, using the same technique as the candidate selectingunit 71 uses in the first embodiment.

Comparing the selection key data items, the candidate selecting unit 160may obtain a finger-contour difference value, a finger region differencevalue and a blood vessel difference value. If this is the case, the unit160 uses the equation (1) as in the first embodiment, thereby settingthe finger-contour difference value, finger region difference value andblood vessel difference value within constant ranges (or normalizingthese values).

Thereafter, the candidate selecting unit 160 uses the finger-contourdifference value, finger region difference value and blood vesseldifference value, thus normalized, and generates evaluation values inunits of registered sets. In this respect, the candidate selecting unit160 which generates evaluation values in units of registered setsdiffers from the candidate selecting unit 71, which generates evaluationvalues in units of individual vein data items.

That is, the vein data items in the respective registered sets pertainto the same person, though they differ from one another. The evaluationvalues found for these vein data items, respectively, are not greatlydifferent and are small if the user to authenticate is the registrant.

If evaluation value E found for only one of the vein data itemscontained in the registered sets is small as shown in FIG. 23, theprobability that the user to authenticate is the registrant is very low.Nevertheless, the candidate selecting unit 71 in the first embodimentmay select, as collation candidate, the vein data for which theevaluation value E is large, prior to the vein data about theregistrant. This may lower the authentication speed.

In view of this, the candidate selecting unit 160 is configured to findthe sum of the reciprocals of values E evaluated by the equation (2) andpertaining to the vein data items in the registered sets, and then touse the sum as the evaluation value for the registered sets as shown inFIG. 24. Since the evaluation value E is the sum of the reciprocals ofvalues E, the probability that the user is the registrant increases inproportion to the evaluation value E.

The candidate selecting unit 160 thus obtains a value evaluated in unitsof vein data items contained in the registered sets. This can prevent adecrease in the collation-candidate selection accuracy, which is causedif the evaluation value E pertaining to the vein data items contained insome of the registered sets is high.

The average of values obtained by the equation (2) or the sum of thesevalues may be utilized to calculate the evaluation value of eachregistered set. In this case, the evaluation value will be too large forthe registered set. The registered set for any person other than theregistrant may then be selected prior to the registered set for theregistrant, lowering the authentication speed. Such an event can beprevented, because the candidate selecting unit 160 uses the sum of the“reciprocals” of the values obtained by using the equation (2).

If the evaluation values are obtained for the respectively registeredsets, the candidate selecting unit 160 selects the selection key dataitems of the registered sets having evaluation values equal to orgreater than the threshold set for the evaluation values and the veindata items which should be registered and which are associated with theselection key data items. The selection key data items and the vein dataitems, thus selected, are used as candidates to collate with the veindata to authenticate. The candidate selecting unit 160 arranges thecollation candidates in an order, as in the same way as the candidateselecting unit 71 does in the first embodiment.

(2-4) Operation and effect

The cellular telephone 100 having the configuration described abovetakes the shift of the finger in lengthwise direction into account, inorder to obtain the finger-contour difference value, i.e., an index forselecting a collation candidate, from the selection key data (coordinatevalue x of finger contour), which represents the finger contour andwhich should be registered, and the selection key data (coordinate valuex of finger contour), which represents the finger contour and whichshould be authenticated. (See the equation (3) and FIGS. 22A to 22C.)

The cellular telephone 100 can therefore obtain the finger-contourdifference value, i.e., one index for selecting a collation candidate,more accurately than in the case where the lengthwise shift of thefinger is not taken into account. Therefore, the vein data of theregistrant is selected as collation candidate, without fail, when theregistrant places his or her finger on the display screen of thecellular telephone 100. As a result, the registrant can be authenticatedat high speed.

In addition, the cellular telephone 100 is structured to prevent theuser's finger placed on the specified position from shifting in thewidthwise direction of the finger (see FIG. 15). That is, the CCD islocated to receive light emitted from the light source 121. Moreprecisely, the CCD is arranged, opposing the light source unit 121across the bases 122, and lies along the upper edge of the LCD 111 andbetween the bases 122 a and 122 b.

Using the selection key data (coordinate value x of finger contour)contained in the video data output from the CCD, the cellular telephone100 obtains the finger-contour difference value, in consideration of thelengthwise shift of the finger. Therefore, any operation needs beperformed to find the widthwise shift of the finger can be omitted. As aresult, the registrant can be authenticated at a higher speed thanotherwise.

In the registration mode, the cellular telephone 100 registers vein dataitems and key data items, all about the same finger, in the form ofregistered sets, each composed of a vein data item and the key data itemassociated therewith. In the authentication mode, the cellular telephone100 selects any candidates of the registered set that should be collatedwith the vein data that should be authenticated.

To be more specific, the cellular telephone 100 calculates the sum ofthe reciprocals of values E obtained by using the equation (2), for thevein data items contained in the respective registered sets (see FIG.24). Although the registered sets are used as units, the influence theevaluation value E imposes on the vein data contained in each registeredset can be more accurately weighted than in the case where the averageor sum of the evaluation values E is calculated.

Therefore, with the cellular telephone 100, the vein data of theregistrant who should be selected as a collation candidate is preventedfrom being not selected as a collation candidate, even though the samefinger of the identical person is placed on the display screen. Thus,the registrant can be identified at high speed.

The configuration described above finds an accurate finger-contourdifference value that is used as an index for selecting a collationcandidate, and obtains an evaluation value from that index, for eachregistered set. The cellular telephone 100 according to the secondembodiment of the present invention can therefore authenticate aregistrant at a higher speed than the authentication apparatus 1.

(3) Other Embodiments

In the embodiments described above, the vein data extracting unit 22having the components 41 to 48 shown in FIG. 4 is used as a unit forextracting the vein data that represents the veins from an imageincluding the veins existing in a finger. The invention is not limitedto this configuration, nevertheless. Various changes may be made inconfiguration. For example, some of the components 41 to 48 may not beused at all or may be replaced by other components. Alternatively,additional processing units may be used. Similarly, the processtechniques the components 41 to 48 perform (e.g., kernel size, etc.) maybe changed.

In the embodiments described above, the data representing the positionwhich the finger contour has at an intermediate stage of extracting thevein data, the data representing the frequency distribution of theregion defined by the finger contour, and the data representing the veinarea of the region defined by the finger contour are extracted. However,the present invention is not limited to this. If the data representingthe position of the finger contour is extracted, any other data may notbe extracted or may be replaced by a different data.

This is because, of the data representing the position which the fingercontour has at an intermediate stage of extracting the vein data, datarepresenting the frequency distribution of the region defined by thefinger contour and data representing the vein area of the region definedby the finger contour, the data representing the position of the fingercontour is the most accurate.

In the embodiments described above, collation candidates are selected byusing the selection key data, and one collation candidate is determinedby using the fixed key data. Nonetheless, the invention is not limitedto this. A collation candidate may be determined by using the selectionkey data. In this case, too, the speed of authentication can beincreased as compared with the conventional authentication technique.

In the embodiments described above, the data (FIG. 7C) representing thedistance from a point in a specific region is utilized as datarepresenting the position of the finger contour. Instead, Bézier curvesor the like may be used to extract a control point, or any othertechniques may be employed.

In the embodiments described above, a luminance histogram is used as thefrequency distribution of the finger region. The invention is notlimited to this, nonetheless. Instead, a histogram may be extracted forall or some of the three primary colors, or any other extractingtechniques may be employed.

In the embodiments described above, the authentication apparatus 1 hasan imaging function (imaging unit 12), a registering function (FIG. 2),and an authenticating function (FIG. 3). However, the present inventionis not limited thereto. Rather, it may be applied to an apparatus thathas one or some of these functions.

The present invention can be utilized in the field of biometricauthentication.

It should be understood by those skilled in the art that variousmodifications, combinations, sub-combinations and alterations may occurdepending on design requirements and other factors insofar as they arewithin the scope of the appended claims or the equivalents thereof.

What is claimed is:
 1. An authentication apparatus comprising: a veindata extracting unit that extracts vein data representing veins, from afirst image including the veins existing in a finger; an extracting unitthat extracts position data representing a position of a contour of thefinger at an intermediate stage of extracting the vein data; and adetermining unit that determines a collation candidate to be collatedwith the vein data, based on similarity between the position data anddata associated with the vein data to be registered.
 2. Theauthentication apparatus according to claim 1, wherein the extractingunit extracts first data representing the position of pixels definingthe contour of the finger, which are spaced at regular intervals, from afirst specific region of a second image generated at the intermediatestage.
 3. The authentication apparatus according to claim 1, wherein theextracting unit extracts second data representing a distance from afirst reference point in the first specific region, with respect to theposition of the pixels spaced at the regular intervals.
 4. Theauthentication apparatus according to claim 3, wherein the determiningunit determines the collation candidate to be collated with the veindata, by using a first difference between a first distance from thefirst reference point in the first specific region and a second distancefrom a second reference point in a second specific region associatedwith the vein data to be registered.
 5. The authentication apparatusaccording to claim 3, wherein the first specific region or the secondspecific region is used as an object to be shifted, and the collationcandidate to be collated with the vein data is determined by using asecond difference obtained every time the first specific region or thesecond specific region used as the object to be shifted is shifted in alengthwise direction of the finger.
 6. The authentication apparatusaccording to claim 1, wherein the vein data extracting unit extracts thevein data from the first image output from an imaging unit that receivesnear infrared light and arranged, opposing a near infrared light sourceacross a display unit that instructs a user to place the finger on asurface extending in a lengthwise direction of the finger.
 7. Theauthentication apparatus according to claim 1, wherein a second imagegenerated at the intermediate stage is generated when a noise componentis removed from the first image by the vein data extracting unit.
 8. Theauthentication apparatus according to claim 1, wherein the extractingunit extracts at least two data items selected from: the position datarepresenting the position of the contour of the finger at theintermediate stage of extracting the vein data, frequency datarepresenting a frequency distribution of a region defined by the fingercontour, and vein area data representing a vein area in the regiondefined by the finger contour.
 9. The authentication apparatus accordingto claim 1, wherein the extracting unit acquires, from the vein dataextracting unit, a second image generated when a noise component isremoved from the first image including the veins existing in the fingerand a binary image represented by binary data, extracts datarepresenting the position of the finger contour from the second image,and extracts, from the binary image, data representing vein area in aregion defined by the finger contour.
 10. An authentication apparatuscomprising: a vein data extracting unit that extracts vein datarepresenting veins, from a first image including the veins existing in afinger; an extracting unit that extracts position data representing aposition of a contour of the finger at an intermediate stage ofextracting the vein data, wherein the extracting unit extracts, from afirst specific region of a second image generated at the intermediatestage of extracting the vein data, first data representing a firstdistance from a first reference point in the first specific region, withrespect to position of pixels spaced at regular intervals, and seconddata representing vein area in a region defined by the finger contour,among the pixels defining the contour of the finger; and a determiningunit that determines a collation candidate to be collated with the veindata, based on similarity between the position data and data associatedwith vein data to be registered, wherein the determining unit determinesthe collation candidate to be collated with the vein data, by using asum of a first ratio and a second ratio, the first ratio being a ratioof a first reference value to an absolute value of a first differencebetween the first distance from the first reference point in the firstspecific region and a second distance from a second reference point in asecond specific region associated with the vein data to be registered,and the second ratio being a ratio of a second reference value to asecond difference between the vein area and the vein area associatedwith the vein data to be registered.
 11. The authentication apparatusaccording to claim 10, wherein the sum is obtained for the vein datacontained in each registered set, and the collation candidate to becollated with the vein data is determined for each registered set byusing summation of reciprocals of the sum in each registered set. 12.The authentication apparatus according to claim 1, further comprising: agenerating unit that acquires a third image represented by binary dataand composed of a background part and a vein part representing veins ofa fixed width from the vein data extracting unit and compresses thethird image, thereby generating a compressed third image, wherein thedetermining unit comprises: a candidate selecting unit that selects thecollation candidate to be collated with the vein data, based onsimilarity between the position data and the data associated with thevein data to be registered; and a candidate determining unit thatdetermines the collation candidate to be collated with the vein data,based on similarity between the compressed third image and a compressedimage associated with the vein data which has been selected as thecollation candidate and which should be registered.
 13. Anauthentication method comprising: extracting vein data representingveins, from a first image including the veins existing in a finger;extracting position data representing a position of a contour of thefinger at an intermediate stage of extracting the vein data; anddetermining a collation candidate to be collated with the vein data,based on similarity between the position data and data associated withthe vein data to be registered.
 14. A registration apparatus comprising:a vein data extracting unit that extracts vein data representing veins,from a first image including the veins existing in a finger; a key dataextracting unit that extracts a plurality of data items representing astate of the finger at one or more intermediate stages of extracting thevein data as key data of a plurality of collation candidates; and aregistering unit that registers, in a storage unit, the vein data inassociation with the key data, wherein the key data extracting unitcomprises: a selection key data extracting unit that extracts datarepresenting a position of a contour of the finger at an intermediatestage of extracting the vein data as the key data for selecting acollation candidate from the plurality of collation candidates; and afixed key data extracting unit that acquires, from the vein dataextracting unit, a third image represented by binary data and composedof a background part and a vein part representing veins of a fixedwidth, to compress the third image, thereby generating a compressedthird image, and extracts the compressed third image as the key data fordetermining the collation candidate from the selected plurality ofcollation candidates.
 15. The registration apparatus according to claim14, wherein the key data extracting unit extracts data representingpositions, which are spaced at regular intervals among pixels definingcontour of the finger, from a specific region of a second imagegenerated at the intermediate stage.
 16. The registration apparatusaccording to claim 15, wherein the key data extracting unit extractsdata representing a distance from a reference point in the specificregion, with respect to the positions of the pixels spaced at theregular intervals.
 17. The registration apparatus according to claim 15,wherein the second image generated at the intermediate stage isgenerated when a noise component is removed from the first imageincluding the veins existing in the finger from the vein data extractingunit.
 18. The registration apparatus according to claim 14, wherein thekey data extracting unit extracts at least two data items selected from:first data representing a position of a contour of the finger at anintermediate stage of extracting the vein data, second data representinga frequency distribution of a region defined by the finger contour, andthird data representing a vein area in the region defined by the fingercontour.
 19. The registration apparatus according to claim 14, whereinthe key data extracting unit acquires, from the vein data extractingunit, a second image generated when a noise component is removed fromthe first image including the veins existing in the finger and a binaryimage represented by binary data, extracts data representing position offinger contour from the second image, and extracts, from the binaryimage, data representing a vein area in a region defined by the fingercontour.
 20. A registration method comprising: extracting vein datarepresenting veins, from a first image including the veins existing in afinger; extracting a plurality of data items representing a state of thefinger at one or more intermediate stages of extracting the vein data askey data of a plurality of collation candidates; extracting datarepresenting a position of a contour of the finger at an intermediatestage of extracting the vein data as the key data for selecting acollation candidate from the plurality of collation candidates;acquiring a third image represented by binary data and composed of abackground part and a vein part representing veins of a fixed width, tocompress the third image, thereby generating a compressed third image;extracting the compressed third image as the key data for determiningthe collation candidate from the selected plurality of collationcandidates; and registering, in a storage unit, the vein data inassociation with the key data.